Financial Entity Recognition with spaCy

Overview

This project focuses on developing a custom Natural Language Processing (NLP) pipeline using the spaCy en_core_web_sm model. The pipeline is designed to accurately identify and extract company names, stock symbols, indexes, and stock exchanges from financial text data.

Features

• Custom NLP Pipeline: Utilizes spaCy's en_core_web_sm model for accurate financial entity recognition.
• Entity Ruler: Developed an entity ruler with special case handling to improve the model's accuracy in financial text analysis.
• Custom Component: Implemented a custom spaCy component to remove unwanted entities, ensuring cleaner and more relevant data output.
• Visualization: Leveraged spaCy's displacy for real-time visualization of named entities, providing clear insights into extracted financial entities.